Adrien Treuille — Building Blazingly Fast Tools That People Love

What this episode covers

Adrien shares his journey from making games that advance science (Eterna, Foldit) to creating a Streamlit, an open-source app framework enabling ML/Data practitioners to easily build powerful and interactive apps in a few hours. Adrien is co-founder and CEO of Streamlit, an open-source app framework that helps create beautiful data apps in hours in pure Python. Dr. Treuille has been a Zoox VP, Google X project lead, and Computer Science faculty at Carnegie Mellon. He has won numerous scientific awards, including the MIT TR35. Adrien has been featured in the documentaries What Will the Future Be Like by PBS/NOVA, and Lo and Behold by Werner Herzog. https://twitter.com/myelbows https://www.linkedin.com/in/adrien-treuille-52215718/ https://www.streamlit.io/ https://eternagame.org/ https://fold.it/ Topics covered: 0:00 sneak peek/Streamlit 0:47 intro 1:21 from aspiring guitar player to machine learning 4:16 Foldit - games that train humans 10:08 Eterna - another game and its relation to ML 16:15 Research areas as a professor at Carnegie Mellon 18:07 the origin of Streamlit 23:53 evolution of Streamlit: data science-ing a pivot 30:20 on programming languages 32:20 what’s next for Streamlit 37:34 On meditation and work/life 41:40 Underrated aspect of Machine Learning 443:07 Biggest challenge in deploying ML in the real world Visit our podcasts homepage for transcripts and more episodes! www.wandb.com/podcast Get our podcast on YouTube, Apple, Spotify, and Google! YouTube: http://wandb.me/youtube Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/google-podcasts Join our bi-weekly virtual salon and listen to industry leaders and researchers in machine learning share their work: http://wandb.me/salon Join our community of ML practitioners where we host AMA's, share interesting projects and meet other people working in Deep Learning: http://wandb.me/slack Our gallery features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, and industry leaders sharing best practices.